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The safety curve for TCAS was generated by varying the sensitivity level of TCAS.
The sensitivity level of TCAS is a system parameter of the logic that increases with
altitude. At higher sensitivity levels, TCAS will generally alert earlier and more aggres-
sively to prevent conflict.
The safety curves show that the DP logic can exceed or meet the level of safety pro-
vided by TCAS while alerting far less frequently. The safety curves can aid in choosing
an appropriate value for the cost of alerting that satisfies a required safety threshold.
Figure 5 also reveals that the DP and Monte Carlo methods for estimating τ offer
similar performance and that they both outperform the simple method, especially when
the cost of alerting is high and the logic can only alert sparingly to prevent conflict. In
the upper-right region of the plot, the three methods are nearly indistinguishable.
1
0 . 98
DP
MC
Simple
TCAS
0 . 96
0
0 . 2
0 . 4
0 . 6
0 . 8
1
Pr(alert)
Fig. 5. Safety curves. Each point on the curves was estimated from 10,000 simulations.
7
Conclusions and Further Work
This paper presented a method for solving large MDPs that satisfy certain assumptions
by decomposing the problem into controlled and uncontrolled subproblems that can
be solved independently offline and recombined online. The method was applied to
airborne collision avoidance and was compared against TCAS, a system that was under
development for several decades and has a proven safety record.
The experiments demonstrate that the collision avoidance logic that results from
solving the MDP using the method presented in this paper reduces the risk of collision
by a factor of 50 while issuing fewer alerts than TCAS in the simulated encounters. The
system reverses less than 1% of the time that TCAS reverses, and the system strength-
ens less frequently as well. It should be emphasized that further simulation studies using
more realistic encounter models are required to quantify the expected performance of
the DP logic [16].
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